Evolution and Neural Network Prediction of CO₂ Emissions in Weaned Piglet Farms

This paper aims to study the evolution of CO₂ concentrations and emissions on a conventional farm with weaned piglets between 6.9 and 17.0 kg live weight based on setpoint temperature, outdoor temperature, and ventilation flow. The experimental trial was conducted during one transition cycle. Generally, the ventilation flow increased with the reduction in setpoint temperature throughout the cycle, which caused a reduction in CO₂ concentration and an increase in emissions. The mean CO₂ concentration was 3.12 g m^-3. Emissions of CO₂ had a mean value of 2.21 mg s^-1 per animal, which is equivalent to 0.195 mg s^-1 kg^-1. A potential function was used to describe the interaction between 10 min values of ventilation flow and CO₂ concentrations, whereas a linear function was used to describe the interaction between 10 min values of ventilation flow and CO₂ emissions, with r values of 0.82 and 0.85, respectively. Using such equations allowed for simple and direct quantification of emissions. Furthermore, two prediction models for CO₂ emissions were developed using two neural networks (for 10 min and 60 min predictions), which reached r values of 0.63 and 0.56. These results are limited mainly by the size of the training period, as well as by the differences between the behavior of the series in the training stage and the testing stage.